Papers with model behavior under meaning-preserving variations
Factual Confidence of LLMs: on Reliability and Robustness of Current Estimators (2024.acl-long)
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| Challenge: | Large Language Models (LLMs) tend to be unreliable on fact-based answers. |
| Approach: | They propose a framework for comparing LLMs' confidence over fact-based answers with hidden-state probes that are more reliable than hidden-status probes. |
| Outcome: | The proposed methods show that hidden-state probes provide the most reliable confidence estimates despite requiring access to weights and supervision data. |